TRANSFORMATION SCIENCE CLASSES WITH ARTIFICIAL INTELLIGENCE AND THE TRADITION OF “SEDEKAH BUMI”: LEARNING ABOUT RENEWABLE ENERGY IN CONTEXT

Yaspin Yolanda; Imam Arif Pribadi

doi:10.22437/jiituj.v10i1.45003

Authors

Yaspin Yolanda Universitas PGRI Silampari https://orcid.org/0009-0009-1122-0053
Imam Arif Pribadi Sriwijaya University https://orcid.org/0009-0005-1484-3759

DOI:

https://doi.org/10.22437/jiituj.v10i1.45003

Keywords:

Contextual, Lesson Study, Renewable Energy, Science Process Skills

Abstract

The lack of scientific literacy among students requires teachers to design interesting lessons and foster students' curiosity about renewable energy. Physics lessons based on ethnoscience through the tradition of “Sedekah Bumi” integrated with Artificial Intelligence are expected to improve scientific process skills. The objectives of this study are (1) to determine the validity of the worksheets in relation to students’ learning barriers, and (2) to determine the improvement in students’ scientific process skills. This study involved 40 students from a senior high school. The research was conducted from April to November 2025. The type of research used was Design Research, consisting of the Preparing for the Experiment, Design Experiment, and Retrospective Analysis stages. Implementation in 3 cycles through Lesson Study between researchers, physics teachers, and students collaborating to design renewable energy learning tools in the form of lesson plans and worksheets. Data collection instruments used tests, questionnaires, observation sheets, and interview guidelines. Data analysis was descriptive with a quantitative mix of tests and reanalyzed qualitatively from the results of interviews, observations, and documentation. The results of the study show (1). Worksheets based on the results of material validation, curriculum of 0.92 (Highly Valid), media validation of 0.89 (Highly Valid) and lesson study expert validation of 0.90 (Highly Valid). (2). The average increase in students' science process skills was 0.83, which is in the high category. Further research is recommended to develop renewable energy modules assisted by Artificial Intelligence through biomass waste to improve students’ science literacy.

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Author Biographies

Yaspin Yolanda, Universitas PGRI Silampari

Department of Physics Education, PGRI Silampari University, Sumatera Selatan, Indonesia

Imam Arif Pribadi, Sriwijaya University

Department of Physics Education, Sriwijaya University, Sumatera Selatan, Indonesia

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